@inproceedings{57177,
  author       = {{Jahneke, Julien and Nolte, Udo and Henkenjohann, Mark and Seidenberg, Tobias and Henke, Christian and Trächtler, Ansgar}},
  booktitle    = {{2024 IEEE Aerospace Conference}},
  publisher    = {{IEEE}},
  title        = {{{Development and Implementation of a Modular Interface for a DroneCAN Communication Bus}}},
  doi          = {{10.1109/aero58975.2024.10521247}},
  year         = {{2024}},
}

@inproceedings{57180,
  author       = {{Lenz, Cederic and Bause, Maximilian and Henke, Christian and Trächtler, Ansgar}},
  booktitle    = {{2024 International Conference on Advanced Robotics and Mechatronics (ICARM)}},
  publisher    = {{IEEE}},
  title        = {{{Boosting Low Data PINN Robustness with Transfer Learning*}}},
  doi          = {{10.1109/icarm62033.2024.10715896}},
  year         = {{2024}},
}

@book{57192,
  author       = {{Bürgel, Christoph and Siepmann, Dirk}},
  publisher    = {{Amazon}},
  title        = {{{Grammatik des gesprochenen und geschriebenen Französisch: Adverbiale, Fürwörter und Verneinung}}},
  volume       = {{4}},
  year         = {{2024}},
}

@inproceedings{56137,
  abstract     = {{Many Android applications collect data from users. The European Union's General Data Protection Regulation (GDPR) requires vendors to faithfully disclose which data their apps collect. This task is complicated because many apps use third-party code for which the same information is not readily available. Hence we ask: how accurately do current Android apps fulfill these requirements?
In this work, we first expose a multi-layered definition of privacy-related data to correctly report data collection in Android apps. We further create a dataset of privacy-sensitive data classes that may be used as input by an Android app. This dataset takes into account data collected both through the user interface and system APIs.
We manually examine the data safety sections of 70 Android apps to observe how data collection is reported, identifying instances of over- and under-reporting. Additionally, we develop a prototype to statically extract and label privacy-related data collected via app source code, user interfaces, and permissions. Comparing the prototype's results with the data safety sections of 20 apps reveals reporting discrepancies. Using the results from two Messaging and Social Media apps (Signal and Instagram), we discuss how app developers under-report and over-report data collection, respectively, and identify inaccurately reported data categories.
Our results show that app developers struggle to accurately report data collection, either due to Google's abstract definition of collected data or insufficient existing tool support. }},
  author       = {{Khedkar, Mugdha and Mondal, Ambuj Kumar and Bodden, Eric}},
  booktitle    = {{In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW ’24)}},
  location     = {{Sacramento, California}},
  title        = {{{Do Android App Developers Accurately Report Collection of Privacy-Related Data?}}},
  doi          = {{10.1145/3691621.3694949}},
  year         = {{2024}},
}

@inproceedings{53665,
  author       = {{Tissen, Denis and Wiederkehr, Ingrid and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}},
  publisher    = {{IEEE}},
  title        = {{{Exploring data-driven model-based systems engineering: a systematic literature review}}},
  doi          = {{10.1109/ictmod59086.2023.10438129}},
  year         = {{2024}},
}

@article{53622,
  abstract     = {{<jats:p>In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life and developing agency in a digital world. This paper presents a qualitative study that explores students’ perspectives on the relevance of learning concepts of data-driven technologies for navigating the digital world. The underlying approach of the study is data awareness, which aims to support students in understanding and reflecting on such technologies to develop agency in a data-driven world. This approach teaches students an explanatory model encompassing several concepts of the role of data in data-driven technologies. We developed an intervention and conducted retrospective interviews with students. Findings from the analysis of the interviews indicate that students can analyse and understand data-driven technologies from their everyday lives according to the central role of data. In addition, students’ answers revealed four areas of how learning about data-driven technologies becomes relevant to them. The paper concludes with a preliminary model suggesting how computing education can make concepts of data-driven technologies meaningful for students to understand and navigate the digital world.</jats:p>}},
  author       = {{Höper, Lukas and Schulte, Carsten}},
  issn         = {{1648-5831}},
  journal      = {{Informatics in Education}},
  keywords     = {{Computer Science Applications, Communication, Education, General Engineering}},
  publisher    = {{Vilnius University Press}},
  title        = {{{Empowering Students for the Data-Driven World: A Qualitative Study of the Relevance of Learning about Data-Driven Technologies}}},
  doi          = {{10.15388/infedu.2024.19}},
  year         = {{2024}},
}

@inproceedings{57209,
  author       = {{Höper, Lukas and Schulte, Carsten}},
  booktitle    = {{Proceedings of the 24th Koli Calling International Conference on Computing Education Research}},
  location     = {{Koli, Finnland}},
  publisher    = {{ACM}},
  title        = {{{New Perspectives on the Future of Computing Education: Teaching and Learning Explanatory Models}}},
  doi          = {{10.1145/3699538.3699558}},
  year         = {{2024}},
}

@inproceedings{55481,
  author       = {{Höper, Lukas and Schulte, Carsten and Mühling, Andreas}},
  booktitle    = {{Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 1}},
  location     = {{Mailand, Italien}},
  publisher    = {{ACM}},
  title        = {{{Students' Motivation and Intention to Engage with Data-Driven Technologies from a CS Perspective in Everyday Life}}},
  doi          = {{10.1145/3649217.3653625}},
  year         = {{2024}},
}

@inproceedings{55656,
  author       = {{Höper, Lukas and Schulte, Carsten and Mühling, Andreas}},
  booktitle    = {{Proceedings of the 2024 ACM Conference on International Computing Education Research - Volume 1}},
  publisher    = {{ACM}},
  title        = {{{Learning an Explanatory Model of Data-Driven Technologies can Lead to Empowered Behavior: A Mixed-Methods Study in K-12 Computing Education}}},
  doi          = {{10.1145/3632620.3671118}},
  volume       = {{10}},
  year         = {{2024}},
}

@inproceedings{56347,
  abstract     = {{<jats:p>The content of university teaching in engineering sciences, particularly in product creation, is characterised by the development of application skills. Changing working conditions require new teaching concepts that are oriented towards the needs of students and practice and consider the acquisition of soft skills. A key method to be considered in this context is the Scenario-Technique. In this paper, a one-day workshop based on a software tool for the Scenario-Technique is presented that focusses on competence development for Scenario-Technique in form of a learning concept. Based on a systematic literature analysis, existing approaches for learning the Scenario-Technique are identified and requirements for a subsequently developed software-supported Scenario-Technique workshop are established. Using a case study, the learning concept is validated in two test phases for comprehensibility, user-friendliness, and practical suitability. The result is a concept that enables practice-oriented learning of the Scenario-Technique.</jats:p>}},
  author       = {{Gräßler, Iris and Tusek, Alena Marie}},
  booktitle    = {{AHFE International}},
  location     = {{Split}},
  publisher    = {{AHFE International}},
  title        = {{{Case study on the software-supported development of competences in Scenario-Technique}}},
  doi          = {{10.54941/ahfe1005548}},
  volume       = {{158}},
  year         = {{2024}},
}

@unpublished{57233,
  author       = {{Weiler, David and Burde, Jan-Philipp and Costan, Kasim and Große-Heilmann, Rike Isabel and Kulgemeyer, Christoph and Riese, Josef and Schubatzky, Thomas}},
  booktitle    = {{PhyDid B - Beiträge zur DPG-Frühjahrstagung 2024 in Greifswald}},
  title        = {{{Förderung digitaler Kompetenzen von Physik-Lehrkräften im ComeNet Physik}}},
  year         = {{2024}},
}

@article{57208,
  abstract     = {{<jats:p> Home delivery failures, traffic congestion, and relatively large handling times have a negative impact on the profitability of last-mile logistics. A potential solution is the delivery to parcel lockers or parcel shops, denoted by out-of-home (OOH) delivery. In the academic literature, models for OOH delivery are so far limited to static settings, contrasting with the sequential nature of the problem. We model the sequential decision-making problem of which OOH location to offer against what incentive for each incoming customer, taking into account future customer arrivals and choices. We propose dynamic selection and pricing of OOH (DSPO), an algorithmic pipeline that uses a novel spatial-temporal state encoding as input to a convolutional neural network. We demonstrate the performance of our method by benchmarking it against two state-of-the-art approaches. Our extensive numerical study, guided by real-world data, reveals that DSPO can save 19.9 percentage points (%pt) in costs compared with a situation without OOH locations, 7%pt compared with a static selection and pricing policy, and 3.8%pt compared with a state-of-the-art demand management benchmark. We provide comprehensive insights into the complex interplay between OOH delivery dynamics and customer behavior influenced by pricing strategies. The implications of our findings suggest that practitioners adopt dynamic selection and pricing policies. </jats:p><jats:p> History: This paper has been accepted for the Transportation Science special issue on TSL Conference 2023. </jats:p><jats:p> Funding: This work was supported by TKI DINALOG. </jats:p>}},
  author       = {{Akkerman, Fabian and Dieter, Peter and Mes, Martijn}},
  issn         = {{0041-1655}},
  journal      = {{Transportation Science}},
  publisher    = {{Institute for Operations Research and the Management Sciences (INFORMS)}},
  title        = {{{Learning Dynamic Selection and Pricing of Out-of-Home Deliveries}}},
  doi          = {{10.1287/trsc.2023.0434}},
  year         = {{2024}},
}

@inproceedings{57250,
  author       = {{Schütze, Christian and Richter, Birte and Lammert, Olesja and Thommes, Kirsten and Wrede, Britta}},
  booktitle    = {{HAI '24: Proceedings of the 12th International Conference on Human-Agent Interaction}},
  isbn         = {{9798400711787}},
  pages        = {{141--149}},
  publisher    = {{ACM}},
  title        = {{{Static Socio-demographic and Individual Factors for Generating Explanations in XAI: Can they serve as a prior in DSS for adaptation of explanation strategies?}}},
  doi          = {{10.1145/3687272.3688300}},
  year         = {{2024}},
}

@article{54907,
  author       = {{Heid, Stefan and Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}},
  issn         = {{0888-613X}},
  journal      = {{International Journal of Approximate Reasoning}},
  publisher    = {{Elsevier BV}},
  title        = {{{Learning decision catalogues for situated decision making: The case of scoring systems}}},
  doi          = {{10.1016/j.ijar.2024.109190}},
  volume       = {{171}},
  year         = {{2024}},
}

@inbook{54623,
  author       = {{Papenkordt, Jörg}},
  booktitle    = {{Artificial Intelligence in HCI}},
  isbn         = {{9783031606052}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Navigating Transparency: The Influence of On-demand Explanations on Non-expert User Interaction with AI}}},
  doi          = {{10.1007/978-3-031-60606-9_14}},
  year         = {{2024}},
}

@inproceedings{55178,
  author       = {{Thommes, Kirsten and Lammert, Olesja and Schütze, Christian and Richter, Birte and Wrede, Britta}},
  title        = {{{Human Emotions in AI Explanations}}},
  year         = {{2024}},
}

@inproceedings{57075,
  author       = {{Assbrock, Agnes and Löhr, Bernd and Bartelheimer, Christian and Beverungen, Daniel}},
  booktitle    = {{International Conference on Information Systems (ICIS)}},
  location     = {{Bangkok, Thailand}},
  title        = {{{Workarounds as Catalysts for Process Innovation: A Multiple Case Study on Pitfalls and Protocols}}},
  year         = {{2024}},
}

@article{57097,
  author       = {{Schroeter-Wittke, Harald}},
  journal      = {{Praktische Theologie}},
  pages        = {{249--252}},
  title        = {{{Chiara Bertoglios Oratorios at the Piano. Zum 200. Geburtstag von Carl Heinrich Reinecke}}},
  volume       = {{59}},
  year         = {{2024}},
}

@article{57028,
  abstract     = {{<jats:p>Lithium niobate and lithium tantalate are among the most widespread materials for nonlinear, integrated photonics. Mixed crystals with arbitrary Nb–Ta ratios provide an additional degree of freedom to not only tune materials properties, such as the birefringence but also leverage the advantages of the singular compounds, for example, by combining the thermal stability of lithium tantalate with the larger nonlinear or piezoelectric constants of lithium niobate. Periodic poling allows to achieve phase-matching independent of waveguide geometry and is, therefore, one of the commonly used methods in integrated nonlinear optics. For mixed crystals, periodic poling has been challenging so far due to the lack of homogeneous, mono-domain crystals, which severely inhibit domain growth and nucleation. In this work, we investigate surface-near (&amp;lt;1μm depth) domain inversion on x-cut lithium niobate tantalate mixed crystals via electric field poling and lithographically structured electrodes. We find that naturally occurring head-to-head or tail-to-tail domain walls in the as-grown crystal inhibit domain inversion at a larger scale. However, periodic poling is possible if the gap size between the poling electrodes is of the same order of magnitude or smaller than the average size of naturally occurring domains. This work provides the basis for the nonlinear optical application of lithium niobate tantalate mixed crystals.</jats:p>}},
  author       = {{Bollmers, Laura and Babai-Hemati, Tobias and Koppitz, Boris and Eigner, Christof and Padberg, Laura and Rüsing, Michael and Eng, Lukas M. and Silberhorn, Christine}},
  issn         = {{0003-6951}},
  journal      = {{Applied Physics Letters}},
  number       = {{15}},
  publisher    = {{AIP Publishing}},
  title        = {{{Surface-near domain engineering in multi-domain x-cut lithium niobate tantalate mixed crystals}}},
  doi          = {{10.1063/5.0210972}},
  volume       = {{125}},
  year         = {{2024}},
}

@inproceedings{57101,
  author       = {{Gräßler, Iris and Rarbach, Sven and Wiechel, Dominik}},
  booktitle    = {{2024 IEEE International Symposium on Systems Engineering (ISSE)}},
  location     = {{Perugia, Italy}},
  publisher    = {{IEEE}},
  title        = {{{Artifact-Oriented Tailoring Approach for Model-Based Impact Analysis}}},
  doi          = {{10.1109/isse63315.2024.10741104}},
  year         = {{2024}},
}